Summary: Rule-based real-time detection of
context-independent events in video shots
Aishy Amer a
Eric Dubois b
Amar Mitiche c
aElectrical and Computer Engineering, Concordia University, MontrŽeal, QuŽebec,
Canada. Email: amer@ece.concordia.ca
bSchool of Information Technology and Engineering, University of Ottawa,
Ottawa, Canada. Email: edubois@uottawa.ca
cINRS-TŽelŽecommunications, UniversitŽe du QuŽebec, MontrŽeal, QuŽebec, Canada.
Email: mitiche@inrs-emt.uquebec.ca
Abstract
The purpose of this paper is to investigate a real-time system to detect context-
independent events in video shots. We test the system in video surveillance envi-
ronments with a fixed camera. We assume that objects have been segmented (not
necessarily perfectly) and reason with their low-level features, such as shape, and
mid-level features, such as trajectory, to infer events related to moving objects.
Our goal is to detect generic events, i.e., events that are independent of the con-
text of where or how they occur. Events are detected based on a formal definition
of these and on approximate but efficient world models. This is done by continually